Beacon-based Localization of the Robot in a Lunar Analog Environment

In-Situ Resource Utilization (ISRU) is a good alternative to enable sustainability in lunar exploration. Toward this objective, Space Applications Services proposed to deploy multiple robots (IBIS, MANTIS, and a mobile gantry) on the Moon for ISRU. The two robots MANTIS and IBIS need to transport the big and heavy components of the mobile gantry to the assembly site cooperatively and assemble them. To finish the task perfectly, it is important for the two robots to get their own precise position in real-time. This paper proposes three localization algorithms that are based on the Extended Kalman Filter (EKF), the triangulation, and the Particle Filter (PF), respectively, for the two robots. All these algorithms use as input the distance measurements from the Ultra Width Band (UWB) devices. All the three localization algorithms have been validated in different environments, including the simulated uneven terrain scenario in Gazebo and the dataset from the filed analog. Experimental results show that the EKF-based localization algorithms can get the best performance in the simulated uneven terrain scenario in Gazebo, while the PF-based one is the best with the dataset from the filed analog.